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London’s Tube and big data: Underground movement

Transport for London gradually learns how to use data

ON JULY 10th London’s train stations simulated some Olympic disruption. Entrances were closed and passengers forced to queue. Chaos ensued, not least because, in addition to the artificial disruption, there was a real one&colon; a Tube train broke down on the Northern Line. But such experiments are beginning to seem outmoded. London’s transport network is now awash with data about both trains and people. The huge potential for improving the system and smoothing people’s journeys is just beginning to be realised.

Transport for London (TfL) already operates one of the world’s largest metropolitan telecoms networks to cope with the huge amounts of data generated by its 270 stations and 530 trains during peak hours. The Oyster card, which most travellers now use to pay for their journeys, allows managers to see where people enter and exit the system. Most strikingly, the Tube’s new Wi-Fi network, which opened in 41 stations on July 4th and will be in 120 by the end of the year, could eventually allow for the tracking of connected smartphones, providing clues to precisely how people move through the system.

Amazon, the online retailer, began by feeding the huge quantities of consumer data it collected back to other consumers (“Customers who bought this book also bought…”). Then it began to use the data to improve its service, through optimised pricing, for example. TfL has followed a similar, but longer, path. It has long mined data to identify problems in its system, although rarely in real time. Gradually, it began to make it available to users. Its website, which details interruptions on lines, attracts 8m unique users a month.

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TfL also pumps out data in machine-readable formats. Some 30 “feeds”, including live departure times and service disruptions, are available for developers to use in smartphone apps and other online services. A recent addition is real-time bus arrival times. “This makes it much easier to jump on a bus when the Tube is down”, explains Malcolm Barclay, whose popular Tube Deluxe and Live Bus Times apps let travellers plan a journey across all modes of public transport.

The network itself is now beginning to steer people. During the Olympics, when the number of daily trips is expected to increase from 12m to about 15m, a special website, getaheadofthegames.com, will be in operation. This will predict how long you will have to wait in a particular station on a particular day and time. Travellers will be able to obtain itineraries that route them around congested parts of the network. The new Wi-Fi network brings all this to the platform.

TfL has given a big chunk of the Oyster card data to the Centre for Advanced Spatial Analysis at University College London. Jonathan Reades, a researcher at the centre, has already identified what he calls the “pulse of the city”. This has turned up odd patterns. In the morning the heaviest commuter flows run north and south, but in the evening there seem to be larger movements west and east. During the Olympics, Mr Reades will try to answer a vital question for TfL&colon; do people actually respond to the advice they receive, or do they often go merrily on their way regardless?